Department of Urology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong , China.
Guangzhou Medical University, Guangzhou, Guangdong , China.
Urol J. 2024 Oct 12;21(5):283-292. doi: 10.22037/uj.v21i.7970.
Our study aims to address two pivotal questions: "What are the recent advancements in understanding the etiology of urological tumors through Mendelian Randomization?" and "How can Mendelian Randomization be more effectively applied in clinical settings to enhance patient health outcomes in the future?"
In our systematic review conducted in April 2023, we utilized databases like PubMed and Web of Science to explore the influence of Mendelian Randomization in urological oncological diseases. We focused on studies published from January 2018, employing keywords related to urological tumors and Mendelian Randomization, supplemented with MeSH terms and manual reference checks. Our inclusion criteria targeted original research studies, while we excluded reports and non-relevant articles. Data extraction followed a PICO-based approach, and bias risk was independently evaluated, with discrepancies resolved through discussion. This systematic approach adhered to PRISMA guidelines for accuracy and thoroughness in reporting.
From the initial 457 publications, we narrowed down to 43 full-text articles after screening and quality assessments. A deeper understanding of Mendelian Randomization can help us explore risk factors with a clear causal relationship to urological tumors. This insight may pave the way for future research in early diagnosis, treatment, and management of associated diseases.
Our review underscores the value of MR in urogenital tumor research, highlighting its efficacy in establishing causality and its potential to clarify disease mechanisms. Despite challenges like large sample sizes and variant identification, MR offers new perspectives for understanding and managing these tumors, suggesting a trend towards more inclusive and diverse research approaches.
本研究旨在解决两个关键问题：“通过孟德尔随机化，我们对泌尿系统肿瘤病因学的理解有哪些最新进展？”以及“孟德尔随机化如何更有效地应用于临床实践，以提高未来患者的健康结果？”
我们在 2023 年 4 月进行了系统综述，利用 PubMed 和 Web of Science 等数据库，探讨孟德尔随机化在泌尿系统肿瘤中的影响。我们专注于 2018 年 1 月以来发表的研究，使用与泌尿系统肿瘤和孟德尔随机化相关的关键词，并辅以 MeSH 术语和手动参考文献检查。我们的纳入标准是原始研究，排除报告和不相关的文章。数据提取采用基于 PICO 的方法，由独立的评估人员评估偏倚风险，并通过讨论解决分歧。该系统方法遵循 PRISMA 指南，以确保报告的准确性和全面性。
从最初的 457 篇文献中，经过筛选和质量评估，我们缩小到 43 篇全文文章。深入了解孟德尔随机化可以帮助我们探索与泌尿系统肿瘤有明确因果关系的风险因素。这一见解可能为相关疾病的早期诊断、治疗和管理的未来研究铺平道路。
我们的综述强调了 MR 在泌尿生殖系统肿瘤研究中的价值，突出了其在建立因果关系方面的功效及其阐明疾病机制的潜力。尽管存在样本量大和变异识别等挑战，但 MR 为理解和管理这些肿瘤提供了新的视角，表明研究方法更加包容和多样化的趋势。
